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Minimum Sum Vertex Cover: Kernelization and Parameterized Algorithms

Authors: Jingyi Liu; Yixin Cao; Ling Gai; Jianxin Wang;

Minimum Sum Vertex Cover: Kernelization and Parameterized Algorithms

Abstract

Given an ordering of the vertices of a graph, the cost of covering an edge is the smaller number of its two ends. The minimum sum vertex cover problem asks for an ordering that minimizes the total cost of covering all edges. We consider parameterized complexity of this problem, using the largest cost~$k$ of covering a single edge as the parameter. Note that the first $k$ vertices form a (not necessarily minimal) vertex cover of the graph, and the ordering of vertices after $k$ is irrelevant. We present a $(k^2 + 2 k)$-vertex kernel and an $O(m + 2^kk! k^4)$-time algorithm for the minimum sum vertex cover problem, where $m$ is the size of the input graph. Since our parameter~$k$ is polynomially bounded by the vertex cover number of the input graph, our results also apply to that parameterization.

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FOS: Computer and information sciences, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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